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• SAS/STAT Procedures A-Z

The NLIN Procedure

• fits nonlinear regression models and estimates the parameters by nonlinear least squares or weighted nonlinear least squares
• allows you to specify the model with programming statements giving you great flexibility in modeling the relationship between the response variable and independent variables
• provides a high-quality automatic differentiator so that you do not need to specify first and second derivatives. You can, however, specify the derivatives if you wish.
• solves the nonlinear least squares problem by one of the following four algorithms (methods):
  • steepest-descent or gradient method
  • Newton method
  • modified Gauss-Newton method
  • Marquardt method
• allows you to confine the estimation procedure to a certain range of values of the parameters by imposing bounds on the estimates
• computes Hougaard's measure of skewness
• obtain separate analyses on observations in groups
• perform weighted estimation
• creates an output data set containing statistics calculated for each observation
• creates a data set containing the parameter estimates at each iteration
• uses ODS to create a SAS data set corresponding to any table
• supports ODS Graphics

For further details see the SAS/STAT User's Guide: The NLIN Procedure
( PDF | HTML )

Examples

• Segmented Model
• Iteratively Reweighted Least Squares
• Probit Model with Likelihood Function
• Affecting Curvature through Parameterization
• Comparing Nonlinear Trends Among Groups
• ODS Graphics and Diagnostics
• Parameter Profiling

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